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Modeling Brain Metastases Through Intracranial Injection and Magnetic Resonance Imaging
Published on: June 7, 2020
Multi-parametric qualitative and quantitative MRI assessment as predictor of histological grading in previously
Simone Sacco1,2, Francesco Ballati1, Clara Gaetani1
1Department of Clinical Surgical Diagnostic and Pediatric Sciences, University of Pavia, Pavia, Italy.
Purpose:
Meningiomas are mainly benign tumors, though a considerable proportion shows aggressive behaviors histologically consistent with atypia/anaplasia. Histopathological grading is usually assessed through invasive procedures, which is not always feasible due to the inaccessibility of the lesion or to treatment contraindications. Therefore, we propose a multi-parametric MRI assessment as a predictor of meningioma histopathological grading.
Methods:
Seventy-three patients with 74 histologically proven and previously treated meningiomas were retrospectively enrolled (42 WHO I, 24 WHO II, 8 WHO III) and studied with MRI including T2 TSE, FLAIR, Gradient Echo, DWI, and pre- and post-contrast T1 sequences. Lesion masks were segmented on post-contrast T1 sequences and rigidly registered to ADC maps to extract quantitative parameters from conventional DWI and intravoxel incoherent motion model assessing tumor perfusion. Two expert neuroradiologists assessed morphological features of meningiomas with semi-quantitative scores.
Results:
Univariate analysis showed different distributions (p < 0.05) of quantitative diffusion parameters (Wilcoxon rank-sum test) and morphological features (Pearson's chi-square; Fisher's exact test) among meningiomas grouped in low-grade (WHO I) and higher grade forms (WHO II/III); the only exception consisted of the tumor-brain interface. A multivariate logistic regression, combining all parameters showing statistical significance in the univariate analysis, allowed discrimination between the groups of meningiomas with high sensitivity (0.968) and specificity (0.925). Heterogeneous contrast enhancement and low ADC were the best independent predictors of atypia and anaplasia.
Conclusion:
Our multi-parametric MRI assessment showed high sensitivity and specificity in predicting histological grading of meningiomas. Such an assessment may be clinically useful in characterizing lesions without histological diagnosis. Key points • When surgery and biopsy are not feasible, parameters obtained from both conventional and diffusion-weighted MRI can predict atypia and anaplasia in meningiomas with high sensitivity and specificity. • Low ADC values and heterogeneous contrast enhancement are the best predictors of higher grade meningioma.
Insights
This study shows that multi-parametric MRI can accurately predict meningioma tumor grade, distinguishing benign from aggressive tumors. Low apparent diffusion coefficient (ADC) values and heterogeneous contrast enhancement are key indicators of higher-grade meningiomas.
Area of Science:
- Neuroradiology
- Oncology
- Medical Imaging
Background:
- Meningiomas are typically benign brain tumors, but some exhibit aggressive behavior (WHO II/III).
- Histopathological grading is crucial but often requires invasive biopsy, which is not always feasible.
- Non-invasive methods are needed to predict meningioma grade.
Purpose of the Study:
- To evaluate a multi-parametric Magnetic Resonance Imaging (MRI) approach for predicting meningioma histopathological grade.
- To determine if MRI parameters can differentiate low-grade (WHO I) from higher-grade (WHO II/III) meningiomas.
Main Methods:
- Retrospective analysis of 74 meningiomas using various MRI sequences (T2 TSE, FLAIR, Gradient Echo, DWI, contrast-enhanced T1).
- Extraction of quantitative diffusion parameters (including intravoxel incoherent motion) and semi-quantitative assessment of morphological features by expert neuroradiologists.
- Statistical analysis including univariate and multivariate logistic regression to identify predictors of tumor grade.
Main Results:
- Significant differences in diffusion parameters and morphological features were observed between low-grade and higher-grade meningiomas (p < 0.05).
- A multivariate model combining MRI parameters achieved high sensitivity (0.968) and specificity (0.925) in discriminating tumor grades.
- Low apparent diffusion coefficient (ADC) values and heterogeneous contrast enhancement were the strongest independent predictors of atypia and anaplasia.
Conclusions:
- Multi-parametric MRI is a sensitive and specific tool for predicting meningioma histopathological grade.
- This non-invasive assessment can aid in characterizing meningiomas when histological diagnosis is not possible.
- Low ADC values and heterogeneous enhancement are key MRI indicators of aggressive meningioma.
